Dupo: A Mixed-Initiative Authoring Tool for Responsive Visualization
Hyeok Kim, Ryan A. Rossi, Jessica Hullman, Jane Hoffswell
摘要
Designing responsive visualizations for various screen types can be tedious as authors must manage multiple chart versions across design iterations. Automated approaches for responsive visualization must take into account the user's need for agency in exploring possible design ideas and applying customizations based on their own goals. We design and implement Dupo, a mixedinitiative approach to creating responsive visualizations that combines the agency afforded by a manual interface with automation provided by a recommender system. Given an initial design, users can browse automated design suggestions for a different screen type and make edits to a chosen design, thereby supporting quick prototyping and customizability. Dupo employs a two-step recommender pipeline that first suggests significant design changes (Exploration) followed by more subtle changes (Alteration). We evaluated Dupo with six expert responsive visualization authors. While creating responsive versions of a source design in Dupo, participants could reason about different design suggestions without having to manually prototype them, and thus avoid prematurely fixating on a particular design. This process led participants to create designs that they were satisfied with but which they had previously overlooked.
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引用它的顶会 Paper4
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- Learning to Automate Chart Layout Configurations Using Crowdsourced Paired ComparisonAoyu Wu, Liwenhan Xie, Bongshin Lee, Yun Wang 等CHI 2021 · 被引用 35 次
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